Machine Learning Engineer (Audio & Signal Processing) Job at Intelliswift - An LTTS Company, Redmond, WA

  • Intelliswift - An LTTS Company
  • Redmond, WA

Job Description

Job Title: Software Engineer II – Machine Learning Engineer (Audio & Signal Processing)

Location: Redmond, WA (Onsite 5 days/week)

Duration: 9 Months (Potential to extend to long term)

Contract: W2

We are seeking a Machine Learning Engineer to support and maintain production-grade machine learning models focused on audio quality evaluation and perceptual audio analysis. This role combines machine learning engineering, model operations, infrastructure support, and cross-functional collaboration.

The ideal candidate has hands-on experience deploying and maintaining ML models in production environments, strong Python and PyTorch skills, and a foundational understanding of audio and signal processing concepts.

Responsibilities

  • Own and support a portfolio of deep learning models throughout their lifecycle, including model architecture, checkpoints, evaluation pipelines, deployment, and monitoring.
  • Maintain and optimize model inference services and production ML workflows.
  • Integrate machine learning services with internal tools and applications through APIs and user-facing interfaces.
  • Monitor model performance, troubleshoot issues, manage deployments, and support service scalability.
  • Analyze model evaluation results and implement improvements, bug fixes, and preprocessing updates.
  • Manage model versioning, checkpoint updates, and release processes.
  • Collaborate with software engineers, researchers, technical program managers, and domain experts to support model users.
  • Participate in operational support and on-call rotations for deployed services.
  • Document workflows, troubleshooting procedures, and best practices.

Minimum Qualifications

  • Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, or a related technical field, or equivalent practical experience.
  • Strong programming skills in Python.
  • Experience with deep learning frameworks such as PyTorch.
  • Understanding of machine learning concepts and ML engineering best practices.
  • Basic knowledge of audio and digital signal processing.
  • Ability to work independently and manage multiple priorities.

Preferred Qualifications

  • Master's or PhD in Computer Science, Electrical Engineering, Audio Engineering, Signal Processing, Speech Processing, Acoustics, or related field.
  • 2+ years of experience deploying and maintaining machine learning models in production environments.
  • Experience operating production services, including monitoring, incident response, troubleshooting, and capacity management.
  • Familiarity with audio concepts such as waveforms, sample rates, frequency analysis, and spectrograms.
  • Experience with audio, speech, acoustic, or perceptual quality evaluation models.
  • Experience building and consuming RESTful APIs.
  • Experience developing lightweight web-based tools or interfaces.
  • Strong communication skills and ability to work with both technical and non-technical stakeholders.

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